In the present environment of heightened concern over criminal and terrorist activities, those skilled in the art have recognized the need for a more widespread application of video surveillance systems. This recognition has resulted in the desire for a more flexible suite of physical video surveillance assets (for example, highly programmable video cameras having the innate ability to handle a multitude of surveillance situations) and firmware for integrating and managing a distributed system of video surveillance assets. U.S. Patent Application Ser. No. 60/618,342, assigned to the same assignee as the present invention, discloses such methods and systems and is hereby incorporated by reference in its entirety as if fully restated herein.
The desire for flexibility also extends to the establishment and management of video surveillance activities. Current systems for establishing and managing video surveillance activities lack flexibility and therefore are difficult to modify to respond to evolving threat environments. In particular, current systems for establishing and managing video surveillance activities were often constructed to respond to a relatively limited number of threats and to perform little or no video analysis. In order to take advantage of the flexibility and programmability of video surveillance cameras and video analysis engines, new video surveillance system architectures are required.
Those skilled in the art desire video surveillance system architectures that adopt a modular approach to video analysis applications and operations. For example, those skilled in the art desire a software and middleware framework that accommodates the rapid addition of video analysis applications to a suite of pre-existing video analysis applications. Such a framework would make it far easier to tailor video surveillance system assets to evolving threat environments.
In addition, state-of-the-art video surveillance systems, particularly those with large numbers of a video surveillance cameras and video analysis engines, create a great deal of video and data. Obviously, it would be prohibitively expensive and impractical to employ a human user to monitor the output each video camera of such a highly integrated and distributed video surveillance system. In addition, it would thwart one of the objectives of such systems, that is, to give a cadre of surveillance system analysts a holistic view of a particular surveillance environment through highly distributed video analysis operations. Instead, the surveillance system analysts would develop only a tunnel vision view of a particular surveillance environment.
Another problem results simply from the number of video cameras that comprise such a distributed and large video surveillance system. Since it would be prohibitively expensive to employ security personnel to monitor each video camera, there must be a system for recording, analyzing and cataloguing the output of the video surveillance system, and for alerting surveillance system analysts in dependence on evolving threats revealed by analysis. Otherwise, the data created by such a system would simply go to waste as so much un-reviewed data.
An additional problem arises from the fact that security system analysts in next generation video surveillance systems will not be continuously monitoring a relatively limited number of video feeds giving them the ability to develop a contextual understanding of fields of view as events evolve in the field of view. Rather, due to the large number of available views, it is simply impossible to monitor all of them. As a result, some way must be devised to analyze, manage, catalogue and present video tracks so that the situational awareness of surveillance system analysts is substantially improved over current video surveillance systems.
Thus, those skilled in the art desire a modular, extensible and distributed video surveillance system architecture that easily accommodates the addition and management of video analysis applications. Those skilled in the art also desire a system for analyzing, managing, cataloguing and presenting video tracks. In particular, those skilled in the art desire a system for assigning meaningful track identifying tags to simplify and ease the cataloguing of such tracks. In addition, those skilled in the art desire a suite of video analysis applications capable of generating a wide degree of track information from key frames suitable for improving the situational awareness of surveillance analysts, to statistical information summarizing monitored object activities and events.